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@ -1197,9 +1197,9 @@ The method executes the SGBM algorithm on a rectified stereo pair. See ``stereo_ |
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stereoCalibrate |
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------------------- |
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.. ocv:function:: double stereoCalibrate( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria term_crit = TermCriteria(TermCriteria::COUNT+ TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC ) |
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Calibrates the stereo camera. |
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Calibrates the stereo camera. |
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.. ocv:function:: double stereoCalibrate( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria term_crit = TermCriteria(TermCriteria::COUNT+ TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC ) |
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.. ocv:pyfunction:: cv2.stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize[, R[, T[, E[, F[, criteria[, flags]]]]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F |
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@ -1287,11 +1287,10 @@ Similarly to :ocv:func:`calibrateCamera` , the function minimizes the total re-p |
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stereoRectify |
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----------------- |
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Computes rectification transforms for each head of a calibrated stereo camera. |
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.. ocv:function:: void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs1, InputArray cameraMatrix2, InputArray distCoeffs2, Size imageSize, InputArray R, InputArray T, OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags=CALIB_ZERO_DISPARITY, double alpha, Size newImageSize=Size(), Rect* roi1=0, Rect* roi2=0 ) |
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Computes rectification transforms for each head of a calibrated stereo camera. |
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.. ocv:cfunction:: void cvStereoRectify( const CvMat* cameraMatrix1, const CvMat* cameraMatrix2, const CvMat* distCoeffs1, const CvMat* distCoeffs2, CvSize imageSize, const CvMat* R, const CvMat* T, CvMat* R1, CvMat* R2, CvMat* P1, CvMat* P2, CvMat* Q=0, int flags=CV_CALIB_ZERO_DISPARITY, double alpha=-1, CvSize newImageSize=cvSize(0, 0), CvRect* roi1=0, CvRect* roi2=0) |
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.. ocv:pyoldfunction:: cv.StereoRectify( cameraMatrix1, cameraMatrix2, distCoeffs1, distCoeffs2, imageSize, R, T, R1, R2, P1, P2, Q=None, flags=CV_CALIB_ZERO_DISPARITY, alpha=-1, newImageSize=(0, 0))-> (roi1, roi2) |
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@ -1374,13 +1373,14 @@ See below the screenshot from the ``stereo_calib.cpp`` sample. Some red horizont |
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stereoRectifyUncalibrated |
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----------------------------- |
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.. ocv:function:: bool stereoRectifyUncalibrated( InputArray points1, InputArray points2, InputArray F, Size imgSize, OutputArray H1, OutputArray H2, double threshold=5 ) |
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Computes a rectification transform for an uncalibrated stereo camera. |
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Computes a rectification transform for an uncalibrated stereo camera. |
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.. ocv:function:: bool stereoRectifyUncalibrated( InputArray points1, InputArray points2, InputArray F, Size imgSize, OutputArray H1, OutputArray H2, double threshold=5 ) |
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.. ocv:pyfunction:: cv2.stereoRectifyUncalibrated(points1, points2, F, imgSize[, H1[, H2[, threshold]]]) -> retval, H1, H2 |
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.. ocv:cfunction:: void cvStereoRectifyUncalibrated( const CvMat* points1, const CvMat* points2, const CvMat* F, CvSize imageSize, CvMat* H1, CvMat* H2, double threshold=5 ) |
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.. ocv:pyoldfunction:: cv.StereoRectifyUncalibrated(points1, points2, F, imageSize, H1, H2, threshold=5)-> None |
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:param points1: Array of feature points in the first image. |
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